abuah retweeted
In July we open-sourced a dynamic graph of everything a child learns in primary school. 1,590 concepts, 3,221 dependencies.
Now we’re turning every concept into interactive experiments kids can play and learn from.
First one, age 7: heat and water.
Everything that used to be a boring textbook can now be an engaging experience, potentially tailored to every child.
Kids education just got a massive upgrade.
abuah retweeted
The games we've long wanted, which didn't exist because they'd cost several times more to make than they'd earn back, will soon become possible. As will the games developers wanted to build, but couldn't with the resources available. It'll be a new golden age of gaming.
It's only been a year.
abuah retweeted
Building apps with GPT-Live-1? Give them a voice that fits.
Here’s how to shape a voice with a prompt or choose from new international preset voices:
For your weekend reading: Build with Pi Durable on Cloudflare, a walkthrough of how to create a multiplayer chat agent, including subagents, on Durable Objects.
earendil.com/posts/pi-durabl…
abuah retweeted
Most of the interesting agent harness work is happening at intersection of harness and infra:
1/ dreaming
2/ async subagents
3/ heartbeats
4/ letting agent schedule reminders
Part of reason im so bullish on managed agents platforms!
All of these in managed deep agents!
abuah retweeted
An overview of how we think about context graphs at @harvey.
Context graphs are a promising direction for improving agent quality and efficiency. We ran a series of experiments on Legal Agent Bench to evaluate how structured context improves online agent performance.
For each LAB task we evaluated, an agent first reviews each document in its client matter and builds a graph of relevant entities and their relationships – e.g. parties, dates, draft vs. executed status, which versions belong to the same contract.
To evaluate the impact of the graph, we compared the performance of an agent with and without the context graph, using LAB’s standard grading setup. Overall, the agent with the context graph improved rubric pass rate by up to 30% while reducing task cost by up to ~50%.
In some cases the graph led to massive improvements. For example, in one firm-knowledge task, the agent was asked to find the firm’s most recent secured financing and retrieve the executed credit and security agreements as precedents for a new facility.
An agent working from raw files attempted to search through several files sequentially, and looked at many different matters, but ultimately selected the wrong precedent (0% of rubric criteria). With the context graph, the same agent found the relevant matter and its executed agreements immediately (75% of rubric criteria).
We’ll have more to share soon on how we’re building this into Harvey, along with more experiments like this one!
abuah retweeted
NPCs can talk back now!
Introducing NPCTalk: make the NPCs of any game talk in realtime. I made every NPC in GTA V answer to me in character, in their own cloned voice, in under 1s, and they act on what you say.
We packaged all the skills Claude learned into a single repo, built on open models: NVIDIA Nemotron ASR for transcription, Qwen 3.8 27B for realtime dialogue, and Fish Audio Drama 3 for the cloned voices, self-hosted on a serverless GPU.
github.com/christos-antono/N…
abuah retweeted
Hi, I'm Felix. I'm an eng lead working on Claude. I love watching people take flight and do things they never thought possible.
We often describe that as "being more ambitious" when using AI, which is tricky advice to follow. I wrote a tutorial:
felixrieseberg.com/how-to-be…
abuah retweeted
1/ muse spark open is the most capable US open-weight model to date.
816B total params, 42B active. 1M-token context. natively multimodal. built for coding and agentic work like long-horizon tasks, hard software engineering, multi-step reasoning.
america! 🇺🇲
abuah retweeted
AI supply chain risk.
🚨 #BREAKING: OpenAI warns employees that spies could be trying to seduce them; women may not be with them for their personalities.
📍Silicon Valley, CA
“If she’s a 6 or above in San Francisco she’s a spy” warned one commentator.
New voices. Better accents. And less "checking..."
GPT-Live-1.1 brings these updates to Voice in ChatGPT, Codex, and dots, with new voices in French, German, Hindi, Mexican Spanish, Korean, and Japanese.
Rolling out today to all users. Coming soon to the API.
Say hello to GPT-Live-1.1
abuah retweeted
Anthropic's research warns rogue AI agents may be months from hijacking smart home devices, copying themselves and spreading without human control.
Its Frontier Red Team split Gemma4-26B-A4B across 15 off-brand Android TV boxes bought for about $55 each, running it at 0.39 tokens per second.
That cluster shows cheap, poorly secured gadgets with 4GB of RAM can jointly host a capable model, since each box holds only 2 of its layers.
The harder test asked models to scan a network, push weights and an agent harness onto new machines, and get inference running on each one.
On a firewalled fleet of 8 emulated Android nodes, only GLM-5.2 completed the full cycle, reaching all 8 nodes in 4 of 5 trials and 7 in the fifth.
GLM-5.2 is too large for TV boxes, but open models under 30B parameters gain 13.7 points a year on the Epoch Capabilities Index, reaching its level by late
They also improve as they spread: when each Qwen3.5-9B instance inherited its predecessor’s notes, setup success rose from 45% to between 61% and 84%.
Speed is the weakness, as a Kimwolf-sized fleet of 2M TV boxes would host roughly 133K model copies producing 80K tokens per second combined, about 40 H100s of compute.
Each new 9B replica would also need about 28 to 51 hours of setup, and that slow, bandwidth-heavy spread would stand out in ISP flow monitoring.
The decisive question is whether a sub-30B model crosses GLM-5.2’s bar before ISPs and device makers coordinate quarantines that no single network can enforce alone.
abuah retweeted
We discovered and communicated with a Chinese AI agent fleet. We believe this is the first time that researchers have ever made contact with a rogue agent fleet in the wild.
Nearly all prior public agent incidents (like the HuggingFace hack) came from American labs. These agents were hosted by Tencent's evaluation research team, and they targeted Alibaba's Amap.
abuah retweeted
We discovered a sophisticated recording device that was hidden inside one of our offices. We used our models to understand the device and where it had come from, identifying that a specific employee had planted it a few days earlier. We referred the matter to the FBI, and we’re grateful to the agents and prosecutors who moved quickly to make an arrest. The FBI’s investigation is ongoing and we will continue to support their work.
At this time, we have no indications of this individual inappropriately accessing or exfiltrating model weights, source code, or customer data. The employee was terminated.
We take protecting our technology, data, and people seriously, and as a matter of national importance. Our security program is designed to protect against a wide range of threat actors, from insider risks to cybercriminals to nation states, and this case is an example of how AI can help address these sophisticated security threats.
abuah retweeted
Claude Coders: You CAN now use your Claude subs in third party harnesses without paying extra.
Works with:
- Claude Agents SDK
- claude -p
- Claude API
- Claude Managed Agents
~6 months ago this would have been HUGE positive news. It still should be.




























